Project assessment system and method

ABSTRACT

A project assessment system comprises a process planning data base, an actual progress information data base, a forecast model data base, a forecast estimation computation device, a project assessment device and a display device of assessment result. The system of the present invention allows assessing the project (clarification of both problems and superior aspects) by using the practical estimation on the basis of quantitative indications.

FIELD OF THE INVENTION

[0001] This invention relates to a project assessment method a andproject assessment system that are for controlling the risk sufferingfrom the execution of projects.

BACKGROUND OF THE INVENTION

[0002] In the conventional project assessment, the determinate of thetotal cost and that of process term for completion have been estimatedon the assumption that the remaining jobs are carried on in compliancewith efficiencies analogous to the process efficiency calculated by theactual progress information up to the time of such project assessment.Referring to the result of the assessment, the project leaders have beenassessing the project by their own experiences and senses. For thepurpose to estimate more precise determinates of the total cost and theprocess term for completion, there is an estimation method forcalculating the determinates such a way that the updated information ofthe process planning and variances regarding to the process termnecessary to carry out each process wherein the variances are assumed tobe constant over the whole processes.

[0003] There are several concrete examples of the conventional methodregarding to the above project assessment such as an estimation methodof a task progress using updated actual progress information (JP,2002-007656, A) and an estimation method using relative precedence/delaycomputed by schedule and progress information of the manufacturingprocess (JP, 2000-237938, A), etc.

[0004] References

[0005] Patent 1: JP publication 2002-007656, A

[0006] Patent 2: JP publication 2000-237938, A

[0007] In the above conventional methods, each process of a project isestimated by predetermined assessment criterion and the information ofthe estimation is used as assistance for the assessment of the project.However, the judgment and identification of the concrete incident dependon the experiences or the senses that the project manager has developedfor his owns and it is difficult to precisely and specify the bottlenecks or the superiorities of the project concerned.

[0008] The forecast estimation of the project has been done with asimple method such as an estimation of the future job hours by using thejob efficiency that has been obtained over all past jobs up to thepresent job, therefore such estimation is sometimes not sufficient forthe forecast estimate of the project to which a complexity of elementalissues is deeply relates.

[0009] Therefore, it is necessary to concretely assess the bottle necksand the superiorities of the project for the purpose of assessment ofthe project. And it is necessary that the fundamental information to beused for the assessment of the project must be refined and improved tocontribute to reflect the practical status of the actual project.

[0010] The purpose of this invention is to provide project assessmentmethod and project assessment system that can serve for the forecastestimate of projects in compliance with the actual progress status andpractical issues.

SUMMARY OF THE INVENTION

[0011] This invention is to solve the above problems and features that aproject assessment system that assesses the forecast estimation of theproject which composes of a plurality of processes comprises a storagedevices to store and retrieve the process planning information of theproject, up-to-date actual progress information and the forecast modelinformation that defines the variance estimation of the majorquantitative parameters, a CPU to calculate the estimate of at least oneof the parameters and evaluate whether the estimate and the mutualcomparison of each process against the estimate satisfy a predeterminedcriteria, respectively, wherein the project status is assessed for eachmoment.

[0012] The above forecast model gives the definitions of the variancesof various critical conditions over processes, starting dates of theprocesses and job volume in the processes by using a probabilitydistribution.

[0013] The forecast estimation is simulated by tracing the actualproject progresses up to the present time to assess the project and theestimates are calculated for the assessment of such forecast of theprojects. The resultant estimation is carried out with the evaluationvalues of the frequency distributions, the mutual correlations and thestandard deviations of the project parameters (as starting dates, endingdates, job volume, man-hour, job materials, job costs). The time-seriesvariation of each project parameter and the result of the comparisonbetween the time-series variation pattern of the project parameters andthat of a typical case when a trouble occurs regarding a selectedsimilar project parameter are calculated for the amendment of suchevaluation values. These evaluation values are served for the projectassessment.

BRIEF DESCTIPTION OF THE DRAWINGS

[0014]FIG. 1 is a drawing that shows a fundamental composition of aproject assessment system.

[0015]FIG. 2 is a computer-process flow that shows the overall presentproject assessment system.

[0016]FIG. 3 is a data format of a Process Planning Data Base.

[0017]FIG. 4 is a data format of an Actual Progress Information DataBase.

[0018]FIG. 5 is a data format of a Forecast Model Data Base.

[0019]FIG. 6 is an explanatory drawing of the graphic presentation forthe selection of the project assessment scheme.

[0020]FIG. 7 is an explanatory drawing of the graphic presentation forthe conditional setting of simulation in forecast estimation.

[0021]FIG. 8 is a computer-process flow that shows the overall processflow of a Forecast Estimation Computation Device.

[0022]FIG. 9 is a computer-process flow that shows the detail processflow of a Forecast Estimation Computation Device.

[0023]FIG. 10 is a computer-process flow that shows the computationprocess for evaluation values in an Estimation of Frequency Distributionselected for a project assessment scheme.

[0024]FIG. 11 is a computer-process flow that shows the computationprocess for evaluation values in an Estimation of Mutual-Correlation ofEstimated Value Pattern selected for a project assessment scheme.

[0025]FIG. 12 is a computer-process flow that shows the computationprocess for evaluation values in an Estimation of Standard Deviationselected for a project assessment scheme.

[0026]FIG. 13 is a computer-process flow that shows the computationprocess for evaluation values in an Estimation of Time-SeriesInformation selected for a project assessment scheme.

[0027]FIG. 14 is a computer-process flow that shows the computationprocess for evaluation values in an Estimation of Fit to PredeterminedPattern selected for a project assessment scheme.

[0028]FIG. 15 is a data format of estimated values.

[0029]FIG. 16 is a data format of evaluation values in an assessmentscheme of frequency distribution.

[0030]FIG. 17 is a data format of evaluation values in an assessmentscheme of mutual-correlation of estimated value pattern.

[0031]FIG. 18 is a data format of evaluation values in an assessmentscheme of standard deviation.

[0032]FIG. 19 is a data format of evaluation values in an assessmentscheme of time-series information.

[0033]FIG. 20 is a data format of evaluation values in an assessmentscheme of fit to predetermined pattern FIG. 21 is a computer-processflow that shows the process flow of a Project Assessment Device.

[0034]FIG. 22 is an explanatory drawing of the graphic presentation of aDisplay Device of Assessment Result for an Estimation of FrequencyDistribution.

[0035]FIG. 23 is an explanatory drawing of the graphic presentation of aDisplay Device of Assessment Result for an Estimation ofMutual-Correlation of Estimated Value Pattern.

[0036]FIG. 24 is an explanatory drawing of the graphic presentation of aDisplay Device of Assessment Result for an Estimation of StandardDeviation.

[0037]FIG. 25 is an explanatory drawing of the graphic presentation of aDisplay Device of Assessment Result for an Estimation of Time-SeriesInformation.

[0038]FIG. 26 is an explanatory drawing of the graphic presentation of aDisplay Device of Assessment Result for an Estimation of Fit toPredetermined Pattern.

[0039]FIG. 27 is a drawing of a composition of a hardware system of aproject assessment system shown in FIG. 1.

PREFERRED EMBODIEMNT OF THE INVENTION

[0040] Using the drawings of the FIG. 1 to the FIG. 27, the details ofthe embodiments of this invention will be explained as followings.

[0041]FIG. 1 shows the fundamental composition of a project assessmentsystem of the first embodiment regarding to this invention. As an actualproject, a construction task in a civil engineering is an objective ofthis project assessment system. The elements of this systemfundamentally comprise a Process Planning Data Base 1, an Actual ProcessInformation Data Base 2, a Forecast Model Data Base 3, a ForecastEstimation Computation Device, a Project Assessment Device and a DisplayDevice for Assessment Result.

[0042] When the project assessment is carried out, the project planninginformation stored in the Process Planning Data Base 1 and the actualprogress information such as the project progress status etc. stored inthe Actual Progress Information Data Base 2 are compared and theup-to-date task status of the project is assessed. For the assessment,the forecast variation defined by a probability distribution model ofthe actual progress information and the various quantitative information(such as task operation term, job volume (defined by quantitativemeasures of working results), workman, job material, elementary unit(=man-hour/material quantities), etc.) is used. The estimate ofvariation of the forecast estimation is computed by the ForecastEstimation Computation Device 4. In addition, the assessment of theproject (as identification and clarification of the problems in theproject planning, etc) is carried out by a quantitative evaluation ofthe estimates in the Project Assessment Device 5 and the assessmentresult is presented on the Display Device for Assessment Result 6.

[0043] Overall process flowchart is shown in FIG. 2. At the judgmentstep (a01), the request for project assessment by the user is checkedand the step goes to the process (a01) if there is no request forproject assessment and to the other process (a02) if there is a requestfor project assessment. At the step (02 a), a project assessment schemecan be arbitrarily selected by the user. At the step (a03), the estimateof variation of the forecast estimation regarding to the variousquantitative information necessary for assessment scheme that isselected at step (a02) is computed. At the step (a04), the projectassessment is carried out on the basis of the project assessment schemeselected at the step (a02) by using the estimates computed at the step(a03). At the step (a05) of display of process assessment result, theresult of the project assessment is carried out at the step (a04) ispresented for the user.

[0044] Further details will be presented using a concrete example in thefollowings. FIG. 3 shows an example of planning data kept in the ProcessPlanning Data Base. The information shown in the column of item isrecorded in the data base for every detail process of the project. Therecorded items are the Process Code 101 uniquely identified (we call“unique number” hereinafter) in the project, the Job Name 102 for whichthe jobs are carried out in the process, the Job Code (unique number)103 which represents the kind of the jobs carried out in the process,the Part Code (unique number) 104 for which the part is the objectivegoods for the jobs of the project, the Contractor Code (unique number)105 for which the contractor operates the job, the Estimated Materials106 that is supplied in the job, the Estimated Workmen 107 served forthe jobs of the process and the Estimated Workdays 108 to complete thejobs carried out in the process, the Estimated Man-days 109 (estimatedworkmen×days) and the Estimated Starting Date 110 to start the operationof the job necessary for the process. Moreover, the recorded itemsinclude Critical Processes in Pre-Sequential Process 111 that is thequantity of processes necessary to be completed before the job carriedout in the process starts, Critical Processes in Post-Sequential Process112 that is the quantity of processes to start after the job carried outin the process is completed, the Critical Starting Date 113 that is theearliest date when the job necessary for the process can start and theCritical Completion Date 114 that is the latest date when the job to becarried out in the project is completed.

[0045]FIG. 4 shows an example of the actual progress data kept in theActual Progress Information Data Base. The contents of the item shown inFIG. 4 regarding to every detail process for each project is recorded.The recorded items are the Actual Materials (accumulation) 201 which isa cumulative quantity of the up-to-date material processed by the jobsthat have bee carried out in the process, the Actual Man-Days(accumulation) 202 which is a cumulative man-days spent up to date forjobs necessary for the process, the Actual Starting Date 203 which isthe start of jobs necessary for the process and the Actual Ending Date204 which is the completion date of the jobs necessary for the process.For these items, the Actual Starting Date 203 and the actual ending date204 are not recorded for the case when the process has not started andcompleted, respectively.

[0046]FIG. 5 shows an example of the model data kept in the ForecastModel Data Base 3. For every kind of jobs carried out in the project,the items shown in FIG. 5 are fundamentally recorded in the ForecastModel Data Base 3. The concrete items for recording are the Job Code 301by which the forecast model is defined, the Average 302 and the StandardDeviation 303 that define the probability distribution (Gaussiandistribution) of the variation regarding to the starting date of the jobdefined by the Job Code 301. The Minimum Allowance 304 and the MaximumAllowance 305 are the definitions of the minimum and the maximumobtained in the above probability distribution regarding to thevariation. The variation of the elementary unit (elementaryunit=man-days/material quantities) of the job which belongs to the kindof jobs defined by the Job Code 301 is defined by the Average 306 andthe Standard Deviation 307 for the probability distribution. The MinimumAllowance 308 and the Maximum Allowance 309 are the definitions of theminimum and the maximum obtained in the above probability distributionregarding to the variation.

[0047] In the estimation of the project parameters computed by theForecast Estimation Computation Device 4, users select the assessmentscheme for the project. FIG. 6 shows an example of the presentation ofthe display to select the assessment scheme. For the assessment schemes,one of estimations as Estimation of Frequency Distribution 401,Estimation of Mutual-Correlation of Estimated Value Pattern 402,Estimation of Standard Deviation 403, Estimation of Time-SeriesInformation 404 and Estimation of Fit to Predetermined Pattern 405 isselected. When End 406 is selected, this system stops to end.

[0048] After selecting the project assessment scheme on the selectiondisplay presentation, the execution conditions for the simulation thatcomputes the estimates of the quantitative values necessary for theassessment scheme prescribed by the forecast estimation shown in FIG. 7are set. The conditions to be set are Simulation Times 407 and DivisionQuantity of Frequency Distribution 408. However, the Division Quantityof Frequency Distribution 408 is only set when Estimation of FrequencyDistribution is selected. After setting the necessary simulationconditions, the simulation process starts by selecting ExecuteSimulation 409. When Back to Initial Setting 410 is selected, thesimulation stops and the display presents the selection graphic for theproject assessment scheme as shown in FIG. 6.

[0049]FIG. 8 shows the computer process flow of Forecast EstimationComputation Device. At the step (411), the variable S that shows thesimulation times is set to be unity. At the step (412), the recordedinformation of the process for which the forecast estimation (414) hasbeen completely carried out is reset. At the step (413), one of theprocesses which are not recorded such that the forecast estimations(414) for the processes among the processes composing the project havebeen completely carried out is selected. At the step (414), theestimated starting date, the estimated elementary unit of the job, theestimated ending date and the estimated man-days are computed. Thedetail contents of the step (414) will be explained in FIG. 9

[0050] At the step for judgment (415), it is judged whether allprocesses have been completed regarding to carrying out the forecastestimation (414) by referring the recording information of thecompletion of such forecast estimation for the processes. If theforecast estimations have not been carried out for all processes thenthe step goes back to the step (413) and if they have been done for allprocesses then the step advances to the step (416). At the step (416),the estimation value computed in the step (414) is processed in responseto the assessment scheme that the user selects on the selection graphicfor assessment scheme as shown in FIG. 6 and the evaluation values forthe project assessment are computed. The details of computer processing(416) according to each assessment scheme are explained in FIG. 10 toFIG. 14. At the step (417), the estimation values and the evaluationvalues computed at steps (414) and (416) are output as the output data,respectively. The formats of the output data will be explained in detailby using FIG. 15 to FIG. 20

[0051] At the step (418), the variable S that indicate simulation timesis incremented with a unity and the at the step (419), the variable Sfor simulation times is judged whether it is more than the simulationtimes (407) set at the execution conditions shown in FIG. 7. If it isequal to or less than the simulation times set at the executionconditions then the step advances to the step (412) and if it is morethen the computer processing of the Forecast Estimation ComputationDevices stops to end.

[0052] The detail computation process flow of the step (414) is shown inFIG. 9. At the judgment step (b01), it is judged by using theinformation stored in the Process Planning Data Base 1 whether theobjective process has the critical processes in pre-sequential processand the step advances to step (b02) if the objective process has thecritical processes in pre-sequential process and advances to step (b03)if the objective process does not have the critical processes inpre-sequential process. At the step (b02), the reference for thestarting date of the objective process is set to be the ending date ofthe critical process (the actual ending date if the objective processhas been completed and the estimated ending date if the objectiveprocess has not been carried out). At the step (b03), the reference forthe starting date of the objective process is set to be the estimatedstarting date. At the step (b04), the estimation value of the varianceof the staring date is computed by using the information of probabilitydistribution model regarding to the variance of the starting dateretrieved from the Forecast Model Data Base 3. More concretely, thereference for the variance is obtained by the equation (1) with thestandard normalized random numbers computed by Molo algorism.

(Reference for Variance)=(Standard Normalized Random Numbers)×(StandardDeviation (300))+(Average (302))  (1)

[0053] After judging whether the reference for the variance obtained bythe equation (1)is within the range between the Minimum Allowance forVariance of Starting Date (304) and the Maximum Allowance for Varianceof Starting Date (305) (Variance of Starting Date)=(Reference forVariance) when the reference for the variance is within such range. And,(Variance of Starting Date)=(Minimum Allowance for Variance of StartingDate (304)) is set if the reference for the variance is smaller than theMinimum Allowance for Variance of Starting Date (304) and (Variance ofStarting Date)=Maximum Allowance for Variance of Starting Date (305)) isset if the reference for the variance is larger than the MaximumAllowance for Variance of. Starting Date (305). At the step (b05), theestimation value of the starting date is obtained by the equation (2).

(Estimation Value of Starting Date)=(Reference for StartingDate)+(Variance of Starting Date)  (2)

[0054] At the judgment step (bO6), it is judged whether the actualprogress information of the similar kind job stored in the ActualProgress Information Data Base 2. If the similar kind job is stored inthe Actual Progress Information Data Base 2 then the step advances tothe step (b07) and if the similar kind job is not stored in the ActualProgress Information Data Base 2 then the step advances to the step(b08). At the step (b07), the reference for the elementary unit of theobjective process is set to be the actual elementary unit (ActualMan-Days/Actual Material Quantities). At the step (b08), the referencefor the elementary unit of the objective process is set to be theestimated elementary unit (estimated Man-Days/estimated MaterialQuantities). At the step (b009), the estimation value of the variance ofthe elementary unit is computed by using the information of probabilitydistribution model regarding to the variance of the elementary unitcorresponding to kind of the job operated in the objective processwherein the model information is retrieved from the Forecast Model DataBase 3. More concretely, the reference for the variance is obtained bythe equation (3) with the standard normalized random numbers computed byMolo algorism.

(Reference for Variance)=(Standard Normalized Random Numbers)×(StandardDeviation (307))+(Average (306))  (3)

[0055] After judging whether the reference for the variance obtained bythe equation (3) is within the range between the Minimum Allowance forVariance of Elementary Unit (308) and the Maximum Allowance for Varianceof Elementary Unit (309), (Variance of Elementary Unit)=(Reference forVariance) when the reference for the variance is within such range. And,(Variance of Elementary Unit)=(Minimum Allowance for Elementary Unit(308)) is set if the reference for the variance is smaller than theMinimum Allowance for Variance of Starting Date and (Variance ofElementary Unit)=Maximum Allowance for Variance of Elementary Unit(309)) is set if the reference for the variance is larger than theMaximum Allowance for Variance of Starting Date (305). At the step(b10), the estimation value of Elementary Unit is obtained by theequation (4).

(Estimation Value of Elementary Unit)=(Reference for ElementaryUnit)+(Variance of Elementary Unit)  (4)

[0056] At the step (b11), the estimated workdays of the objectiveprocess is obtained by the equation (5).

(Estimated Workdays)=(Estimated Elementary Unit)×(Estimated Materials(106))  (5)

[0057] By using this estimated workdays, the estimated ending date isobtained by the equation (6).

(Estimated Ending Date)=(Estimated Starting Date)+(EstimatedWorkdays)  (6)

[0058] At the step (b12), it is evaluated whether the estimated startingdate obtained at the step (b05) and the estimated ending date obtainedat the step (b11) satisfy the critical term set for every process storedin the Process Planning Data Base 1. The amendment is done as (EstimatedStarting Date)=(Critical Starting Date (113)) if the estimated startingdate is earlier than the critical starting date and (Estimated EndingDate)=(Critical Completion Date (114)) if the estimated ending date islater than the critical completion date (114).

[0059] At the step (b13), the estimated man-days necessary for thecompletion of the job of the objective process is computed. It is set as(Estimated Man-days)=(Estimated Workmen (117)) if an amendment has notbeen done using the critical term in the step (b12) and the estimationman-days is given by the equation (7) if an amendment has been doneusing the critical term in the step (b12).

(Estimated Man-Days)=(Estimated Elementary Unit)×(EstimatedMaterial)/Amended Workdays  (7)

[0060]FIG. 10 shows the details of the computer process flow (401) whenthe estimation of frequency distribution (401) is selected for theassessment scheme. At the step (c01), the division unit of the frequencydistribution information is obtained by dividing the differences betweenthe maximum and the minimum for every estimation value with the divisionquantity of the frequency distribution. The frequency distributioninformation is complied by assembling computation result of theestimation values against the simulation times for each of the abovedivision unit.

(Evaluation Value)=(99% VaR (A))/(Estimated Maximum Frequency (B))  (8)

[0061] By using this estimation of the frequency distribution, thesensitivity of (99% VaR) is estimated for the large value risk againstthe average of the estimation values.

[0062] The details of the computer process flow at the step (416) willbe shown when the Estimation of Mutual-Correlation of Estimated Valuepattern (402) is selected for the project assessment scheme shown inFIG. 11. At the step (c03), an arbitral process that is a component ofthe project is selected. At the step (c04), the plurality of theestimation values obtained for the process selected in the step (c03) issequentialized, for example, in a form of (Estimated Starting Date,Estimated Ending Date, Estimated Elementary Unit, Estimated Man-Days) asequence X. An element (Estimated Starting Date for example) which is acomponent of the sequence X is chosen as a reference estimation and itis set to be unity and the rests of the numbers are normalized with suchreference estimation.

[0063] At the step (c05), one of the processes other than the processselected in the step (c03) is selected. At the step (c06), the pluralityof estimation values of the process selected in the step (c05) issequentiallized in a form such as Estimated Starting Date, EstimatedEnding Date, Estimated Elementary Unit, Estimated Man-Days as a sequenceY. An element (Estimated Starting Date for an example) which is acomponent of the sequence Y is chosen as a reference estimation and itis set to be unity and the rests of the numbers are normalized with suchreference estimation. In this normalization, the kind of the estimationvalues that are components of the sequence Y, the order of theestimation values in the sequence and the reference estimation to beselected from the estimation values are computed in the same manner asshown in the step (c04).

[0064] At the step (c07), a mutual-correlation between the sequence Xobtained in the step (c04) and the sequence Y obtained in the step (c06)is computed. More concretely, the ensemble averages, and the squarevariances of X and Y are defined as E(X), E(Y), V(X) and V(Y),respectively,

(Mutual-Correlation)=E((X−E(X)(Y−E(Y))/({square root}V(X){squareroot}V(Y))  (9)

[0065] At the judgment step (c08), it is judged whether all processesother than the process selected in the step (c03) have been computed.The step goes back to the step (c05) if all processes other than theselected process have not been computed and the step advances to thestep (c09) if all processes other than the selected process have beencomputed. At the judgment step (c09), it is judged whether all processescomposing the project have been computed. The step goes back to the step(c03) if all processes have not been computed and the computationalprocess flow (416) stops to end if all processes have not been computed.

[0066] By using this mutual correlation of the estimation of themutual-correlation of estimated value pattern, it is possible toevaluate the coefficients of the mutual-correlation for each pair ofprocesses.

[0067]FIG. 12 shows the details of the computer process flow (416) whenthe Estimation of Standard Deviation (403) is selected for the projectassessment scheme. The following computer processes are done for allestimation values (Estimated Starting Date, Estimated Ending Date,Estimated Elementary Unit, etc.) which are the objective values forevaluation regarding the objective processes.

[0068] At the step (c10), the standard deviations (A) of the aboveestimation values are computed by using the each simulation times foreach estimation value. At the step (c11) an arbitral process which is acomponent of the objective process is selected. At the step (c12), thestandard deviation values (B) of the above estimation values by usingthe information of the project excluding the project selected in thestep (c11) are computed. At the step (c13), the evaluation value iscomputed by using the equation (19) with the standard deviation (A)computed in the step (c10) and the standard deviation computed in thestep (c12).

(Evaluation Value)=(Standard Deviation A)/(Standard Deviation B)

[0069] At the judgment step (c14), it is judged whether all processescomposing the objective project have been computed. The step goes backto the step (c13) if all processes have not been computed and thecomputational process flow (416) stops to end.

[0070] It is possible to assess the influence of each process againstthe all standard deviation by using this estimation of the standarddeviation.

[0071]FIG. 13 shows the details of the computer process flow (416) whenthe Estimation of Time-Series Information (404) is selected for theproject assessment scheme. The following computer processes are done forall estimation values (Estimated Starting Date, Estimated Ending Date,Estimated Elementary Unit, etc.) which are the objective values forevaluation regarding the objective processes.

[0072] At the step (c15), the estimation values for an arbitralclassification patter (workmen, work area, objective part used in thejob, etc.) of every group of the processes composing the project arecomputed for every one week and the estimation values are sequentializedin a form of time-series (X). At the step (c16), an arbitralclassification pattern is selected among the above classificationpatterns. At the step (c17), an arbitral classification patterns otherthan the pattern selected in the step (c16) is selected. At the step(c18), the mutual-correlation between the time-series information X(computed in the step (c15)) of the classification pattern selected inthe step (c16) and the time-series information Y (computed in the step(c15)) of the classification pattern selected in the step (c17).

[0073] At the judgment step (c19), it is judged whether allclassification patterns other than the classification pattern selectedin the step (c16) have been computed. The step goes back to the step(c17) if all classification patters other than the classification patterselected in the step (c16) have not been computed and the step advancesto the step (c20) if all classification patterns other than theclassification patter selected in the step (c16) have been computed. Atthe judgment step (c20), it is judged whether all classificationpatterns have been computed. The step goes back to the step (c16) if allclassification patters have not been computed and the computationalprocess flow (416) stops to end if the all classification patterns havebeen computed.

[0074] By using this estimation of the time-series information, it ispossible to evaluate the coefficients of the mutual-correlation for eachpair of classification patterns in a view of the time-seriesinformation.

[0075]FIG. 14 shows the details of the computer process flow (416) whenthe Estimation of Fit to Predetermined Pattern (405) is selected for theproject assessment scheme. At the step (c21), a simulation is done basedon the predetermined critical pattern (Shortage of Man-Days, Delay ofCompletion, Large Change of Specifications, Large Supplementation ofSpecifications) as a possible incidental problem to occur the project.The simulation is carried out for every critical pattern, for example,the delivery schedule of parts to be used for the job consistently has a10% delay for the case of delay of completion. Every estimation valuefor the simulation (as Process Term, Elementary Unit, Cost, Man-Days,etc.) for every one week is sequentialized for every critical pattern.

[0076] At the step (c22), the simulation is carried out based on theinformation of the actual progress of the project and every estimatedvalue for every one week is sequentialized. At the step (c23), one ofthe patterns is arbitrarily selected. At the step (c24), X that belongsto the critical pattern selected in the step (c23) and Y that iscomputed in the step (c22) both among the time-series informationcomputed in the step (c21) are selected for every estimatedvalue and themutual correlation coefficient given by the equation (9) is computed. Atthe judgment step, it is judged whether all of the predeterminedcritical patterns have been processed and the step goes back to the step(c23) if all critical patters have not been computed and thecomputational process flow (416) stops to end if the all criticalpatterns have been computed.

[0077] By using this assessment scheme as the estimation of the fit tothe predetermined pattern, it is possible to evaluate how much thepresent project fits to the predetermined pattern.

[0078]FIG. 15 shows the format of the output data regarding to theestimated values output at the step (417). In this simulation, theestimated values (the estimated value of starting date (420) and theestimated value of ending date (421) etc.) is computed by the simulationfor every one week and the results are output. The computed results areoutput in an amount of the simulation times as users have set.

[0079]FIG. 16 shows the format of the output data of the evaluationvalues output in the step (417) when the Estimation of FrequencyDistribution (401) is selected for the project assessment scheme. As formore details, the evaluation values computed in the step as shown inFIG. 10 for the computed estimated values (Starting Date (422), EndingDate (423), Elementary Unit (424), Man-Days (425)) are output.

[0080]FIG. 17 shows the format of the output data of evaluation valuesoutput in the step (417) when the Estimation of Mutual-Correlation ofEstimated Value Pattern (402) is selected for the project assessmentscheme. As for more details, the Mutual-Correlation Coefficients (426)between two processes that are components of the objective project areoutput as evaluation values in a matrix form as shown in FIG. 17.

[0081]FIG. 18 shows the format of the output data of the evaluationvalues output in the step (417) when the Estimation of StandardDeviation (403) is selected for the project assessment scheme. As formore details, the Evaluation Values (427) that consist of the standarddeviations computed by the information excluding an arbitral process andthe standard deviation computed by the information including allprocesses are output against the index that is the process arbitrarilyexcluded in such computation as shown in FIG. 18.

[0082]FIG. 19 shows the format of the output data of the evaluationvalues output in the step (417) when the Estimation of Time-SeriesInformation (404) is selected for the project assessment scheme. As formore details, the mutual-correlation coefficients for job groupscomputed for the estimated values (Elementary Unit (428), AccumulationMan-Days (429), Accumulation Day (430), Accumulation Cost (4331), etc.)computed in the computer process as shown in FIG. 13 are output asevaluation values in a matrix form as shown in FIG. 19.

[0083]FIG. 20 shows the format of the output data of the evaluationvalues output in the step (417) when the Estimation of Fit toPredetermined Pattern (405) is selected for the project assessmentscheme. As for more details, the fit is computed regarding to theestimated values (Task Operation Term (432), Elementary Unit (428), Cost(434), Man-Days (435), etc.). The mutual-correlation coefficientsbetween the estimated values of whole project and the estimated valuescomputed by the simulation carried out under the critical patterns(Shortage of Man-Days (436), Delay of Completion (437), etc.) iscomputed by the computer process flow as shown in FIG. 14 are output ina matrix form as shown in FIG. 20.

[0084]FIG. 21 shows the computer process flow implemented by the processassessment device regarding to the present invention. At the step (501),a preparatory setting is done for the selection of the projectassessment scheme among the Estimation of Frequency Distribution (401),the Estimation of Standard Deviation (403), the Estimation ofMutual-Correlation of Estimated Value Pattern (402), Estimation ofTime-Series Information (404) or Estimation of Fit to PredeterminedPatter (405). For the cases of the Estimation of Frequency Distribution(401) or the Estimation of Standard Deviation (403), the step goes tothe step (502) and for the cases of the Estimation of Mutual-Correlationof Estimated Value Pattern (402), Estimation of Time-Series Information(404) or Estimation of Fit to Predetermined Patter (405), the step goesto the step (503). At the step (502), it is judged whether theevaluation values are more than the references set for the estimatedvalues. At the step (503), it is judged whether the computedmutual-correlation coefficients are more than the predeterminedreference.

[0085]FIG. 22 shows an example of graphic display presentation in theDisplay Device of Assessment Result 6 when the Estimation of FrequencyDistribution (401) is selected for the project assessment scheme. In thedisplay box for the assessment scheme (601), the information of theselected project assessment scheme is displayed (this is common to theexamples shown below). In the selection menu of the estimated values602, an estimated value is selected among a list of computed estimatedvalues. In the display box of the frequency distribution, the histogramof frequency distribution of the estimated values selected in theselection menu 602 is presented. In the display box for evaluationinformation 505, the evaluation values 604 of the estimated valuesselected in the estimated value selection menu and the evaluation valuesevaluated in the Project Assessment Device 5 are displayed. When the“back to top” button 606 is selected, the display goes back to theselection of the project assessment (this is same as for the followingexamples of the graphic display presentation).

[0086] In this method, the project can be assessed by using the graphicpattern presented by the histogram of the frequency distribution of theselected estimated values.

[0087]FIG. 23 shows an example of graphic display presentation in theDisplay Device of Assessment Result 6 when the Estimation ofMutual-Correlation of Estimated Value Pattern (402) is selected for theproject assessment scheme. In the selection menu of reference process(607), a process which can be the reference for evaluation is selectedfrom a list of menu that includes the processes composing the project.In the display box of evaluated values, the process names and themutual-correlation coefficients 608 for the process groups that have thelarger mutual-correlation coefficients than the predetermined values andthe assessment results 609 of the mutual-correlation coefficientsobtained by the Project Assessment Device 5.

[0088] In this method, the project can be assessed by obtaining theestimated variance of the other process that has a positivemutual-correlation with the estimated variation pattern of the referenceusing the graphic pattern presented by the histogram of the frequencydistribution of the estimated values that have been selected.

[0089]FIG. 24 shows an example of graphic display presentation in theDisplay Device of Assessment Result 6 when the Estimation of StandardDeviation (403) is selected for the project assessment scheme. In thedisplay box for the assessment information, the name and the evaluationvalues 610 of the project that is excluded in the evaluation values andthe results 611 that are assessed by the Project Assessment Device 5.

[0090] In this method, the project can be assessed by computing thestandard deviations of summation of all process against an arbitralestimated variance subtracted by the above estimated variance based onthe plurality of estimation results and subtracting among these standarddeviations.

[0091]FIG. 25 shows an example of graphic display presentation in theDisplay Device of Assessment Result 6 when the Estimation of Time-SeriesInformation (404) is selected for the project assessment scheme. In theselection menu of reference process 612, a process which can be thereference for evaluation is selected from a list of menu that includesthe processes composing the project. In the selection menu of theestimated values 613 that is an objective to be evaluated, the estimatedvalues are selected from a list of a menu that includes the computedestimated values. In a display box of evaluated values information, themutual-correlation coefficients of the time-series information of theestimated values that are selected from the selection menu of theestimated values 613 that is an objective to be evaluated, wherein thecoefficients are larger than a certain value, are assessed by theProject Assessment Device 5 for the reference process selected in theselection menu 612 of reference process. The name of the process, themutual-correlation coefficient 614 and the result 615 of themutual-correlation coefficient are displayed.

[0092] In this method, the project can be assessed by using thetime-series data of the actual progress information up to the assessmenttime, the time-series estimated variances after the assessment time andthe mutual-correlation information between every two processes.

[0093]FIG. 26 shows an example of graphic display presentation in theDisplay Device of Assessment Result 6 when the Estimation of Fit toPredetermined Pattern (405) is selected for the project assessmentscheme. In the display box 616 for the mutual-correlation with apredetermined pattern, the coefficient of mutual correlation with everycritical pattern (Shortage of Man-Days, Delay of Completion, LargeChange of Specifications, Large Supplementation of Specifications) foreach of estimated value (Task Operation Term, Elementary Unit, Cost,Man-Days, etc.) is displayed in a form of a matrix. In the display boxfor evaluation information, the name 617 of the critical pattern, ofwhich average of the coefficient of the mutual-correlation with theestimated value for every critical pattern is larger than apredetermined value, and the average of the coefficients of themutual-correlations are displayed.

[0094] In this method, a critical ranges are set for the variation ofparameters regarding starting date, ending date, job volume, man-days,job materials, cost. Then the project can be assessed by computing thedegree of the mutual correlation the group of time-series data and byusing the critical information for the highly correlated results.

[0095] The embodiments that have been explained above are discussed withexamples of construction tasks in a civil engineering, etc. However, thepresent invention is not limited within these examples but applicable tothe project assessment of software program development, the processassessment of the operation schedules of traffic vehicles, the processassessment of the semiconductor manufacturing process, etc.

[0096]FIG. 27 shows a hardware design to actually systematize thepresent computer process flow regarding to the present invention. Thesystem is constructed a computer comprising a CPU 10, a Memory Device20, a Storage Device 30, an Input Device 40 and an Output device 50. Theprogram regarding this invention and the data base stored in the StorageDevice 30 are transferred to a Memory Device 20, the Input Data of theproject given by the Input Device 40 is computer-processed in CPU 10based on the instruction information input through the Input Device 40and the result is displayed on the Output Device 50. The Input Device 40includes communication apparatus through which the input data sent onthe network are received.

[0097] In comparison to FIG. 1, the Process Planning Data Base 1, theActual Progress Information Data base 2 and the Forecast Mode Data Baseare stored in the Storage Device 30. The procedures for the projectassessment method of which fundamental concept is drawn out in FIG. 2and the detail operation and the functions described in FIG. 8 to FIG.14 and FIG. 21 are stored in the storage device 30 as a set of computerprograms. The Forecast Estimation Computation Device 4 and the ProjectAssessment Device 5 are realized by the CPU 10 and the Memory Device 20.The Display Device of Assessment Result is realized by the Output Device50.

[0098] The present invention allows assessing the project (clarificationof both problems and superior aspects) using the practical estimation onthe basis of quantitative indications.

What is claimed is:
 1. A project assessment system that assists toassess a project consisting of plurality of processes by computingforecast estimates of saidproject based on a set of information asstarting information, progress information and up-to-date information ofsaid project comprising: a computer process that computes, by usingprocess planning information of said project, up-to-date actual progressinformation of said project and forecast model information of saidproject that defines estimates of variances of a plurality of parametersthat are substantial measures of said project, at least one ofestimation values of said parameters of said each process and anothercomputer process that enables to assess said project by judging whethersaid estimation values satisfy a predetermined criterion or a result ofa mutual comparison of said estimation values against each differentprocess satisfies a predetermined criterion.
 2. A project assessmentsystem as defined in claim 1, wherein said parameters include at leastone of parameters among starting date, ending date, job volume,workdays, man-days, material quantities and cost.
 3. A projectassessment system as defined in claim 1, wherein said estimates ofvariances of said parameters are defined in a probability distribution,said computer process has functionalities to compute forecast estimatesof variances of a plurality of parameters by using random numbers and tomake a graphical presentation of said forecast estimates and saidanother computer process assesses said project by using said graphicalpresentation.
 4. A project assessment system as defined in claim 1,wherein said estimates of variances of said parameters are defined by aprobability distribution, said computer process has functionalities tocompute forecast estimates of variances of a plurality of parameters byusing random numbers and to compute forecast estimates of otherprocesses that have positive mutual-correlation against variationpattern of an estimate of a variance of an arbitral parameter of anarbitral process based on a plurality of said forecast estimatesobtained by generating a plurality of random number sets and saidanother computer process assesses said project by using said forecastestimates of other processes.
 5. A project assessment system as definedin claim 1, wherein said estimates of variances of said parameters aredefined by a probability distribution, said computer process hasfunctionalities to compute forecast estimates of variances of pluralityof parameters by using random numbers and to compute a standarddeviation of summation of all processes against an estimate of avariances of an arbitral parameter of an arbitral process and a standarddeviation of a summation of processes subtracted a specific process fromall processes based on a plurality of said forecast estimates obtainedby generating a plurality of random number sets and said anothercomputer process assesses said project by using said forecast estimatesof other processes.
 6. A project assessment system as defined in claim1, wherein said compute process computes time-series data of said actualprogress of variances of said parameters up to a time to carry outassessment and a time-series data of said estimates of variances of saidparameters from time from a time to carry out assessment to a futuretime and said another computer process assesses information of mutualcorrelations between said time-series data of each pair of processes 7.A project assessment system as defined in claim 1, wherein said computerprocess computes, by using a group of time-series data consisting oftime-series data of said actual progress of variances of said parametersup to a time to carry out assessment and time-series data of saidestimates of variances of said parameters from a time to carry outassessment to a future time, a degree of mutual correlation of a saidgroup of time-series data by setting a specific critical condition forvariation range of said at least one of said parameters among startingdate, ending date, job volume, workdays, man-days, material quantitiesand cost and said another computer process assesses said project byusing said information of said specific critical condition set for aresultant high mutual-correlation.
 8. A project assessment system thatassists to assess a project consisting of plurality of processes bycomputing said forecast estimates of said project based on a set ofinformation of starting information, progress information and up-to-dateinformation of said project, comprising: a process planning data baseincluding process planning information of said project, an actualprogress information data base including up-to-date actual progressinformation of said project, a forecast model data base includingforecast model information of said project that defines at least one ofestimates of variances of a plurality of parameters that are substantialmeasures of said project, a forecast estimation computation device thatcomputes an estimate of a variance of forecast estimation of saidparameters and a project assessment device to assess said project basedon said estimates and a selected assessment scheme.
 9. A projectassessment system as defined in claim 8, wherein said forecastestimation computation device has functionalities to compute an estimateof a variance of said forecast estimation of said parameters and tooutput processed values regarding to said forecast estimation as anevaluation value in response to said selected assessment scheme.
 10. Aproject assessment system as defined in claim 8, wherein said projectassessment device is a computer device comprising; a storage device tostore said process planning data, said actual progress information database and said forecast model data base, a CPU that realizes functions assaid forecast estimation computation device and said project assessmentdevice and a display device to output an assessment result as an outputdevice.
 11. A project assessment system as defined in claim 8, whereinsaid project assessment device is a computer device comprising; astorage device to store said process planning data, said actual progressinformation data base and said forecast model data base, a CPU thatrealizes functions as said forecast estimation computation device andsaid project assessment device and a display device of an assessmentresult that has a graphic display presentation for selecting a projectassessment scheme by which selection of a project assessment scheme iscarried out through an input device.
 12. A project assessment method bywhich an assist is carried out to assess a project consisting ofplurality of processes by computing the forecast estimates of saidproject based on a set of information as starting information, progressinformation and up to date information of said project, comprising: astep that memorizes process planning information of said project,up-to-date actual progress information of said project and forecastmodel information of said project that defines estimates of variances ofa plurality of parameters that are substantial measures of said project,at least one of said parameters of said estimation values of eachprocess, another step to compute at least one of parameters amongstarting date, ending date, job size, workdays, man-days, materialquantities and cost by using said process planning information, saidactual progress information and said forecast model information and ajudgment step to judge whether said estimate satisfies a predeterminedcriterion or a result of a mutual comparison of said estimation valueagainst each different process satisfies a predetermined criterion,wherein at least one of said parameters is assessed on the basis of aresult obtained in said judgment step.
 13. A project assessment methodas defined in claim 12, wherein said estimates of variances of saidparameters are defined by a probability distribution, a step to computeforecast estimates of variances of a plurality of parameters by usingrandom numbers and a step to compute a plurality of said forecastestimates of variances obtained by generating a plurality of randomnumber sets are further included and said judgment step assess saidproject.
 14. A project assessment method as defined in claim 12, whereina step to compute an estimate of starting date as said at least one ofparameters has functions to judge whether a objective process has apre-sequential order limited process by using information of saidprocess planning and to resultantly set an ending date of saidpre-sequential order limited process as a reference for starting date ofsaid objective process for a case that said objective process has saidpre-sequential order limited process and set a starting date ofestimated starting date of said process as a reference for starting dateof said objective process for a case that said objective process doesnot have said pre-sequential order limited process, to extractinformation of probability distribution model of a variance of startingdate from said forecast model information of said project, to compute astandard normalized random number set by a simulation based on avariance of starting date, to compute a reference for a variance byusing said standard normalized random number set and to judge whethersaid reference for a variance is in a range of a variance of startingdate based on said forecast model information of said project so thatadding said reference for variance as a variance of starting date tosaid reference for starting date for a case that said reference for avariance is in a range of a variance of starting date, and said estimateof starting date is obtained therein.
 15. A project assessment method asdefined in claim 12, wherein a step to compute an estimate of elementaryunit (man-days/material quantities) as said at least one of parametershas functions to judge whether a similar kind job to an objectiveprocess is stored in said actual progress information data base and toresultantly set an actual elementary unit for a reference for aelementary unit for a case that a similar kind job to an objectiveprocess is stored in said actual progress information data base and seta planned elementary unit for a reference for a elementary unit for achase that a similar kind job to an objective process is not stored insaid actual progress information data base, to extract information ofprobability distribution model of a variance of an elementary unit fromsaid forecast model information of said project, to compute a standardnormalized random number set by a simulation based on a variance of saidelementary unit, to compute a reference for a variance by using saidstandard normalized random number set and to judge whether saidreference for a variance is in a range of a variance of elementary unitbased on said forecast model information of said project so that addingsaid reference for variance as a variance of elementary unit to saidreference for said elementary unit for a case that said reference for avariance is in a range of a variance of said elementary unit andestimate of starting date is obtained in said steps therein.
 16. Aproject assessment method as defined in claim 15, wherein a step tocompute an estimate of starting date as said at least one of parametershas functions to judge whether a objective process has a pre-sequentialorder limited process by using information of said process planning andto resultantly set an ending date of said pre-sequential order limitedprocess as a reference for starting date of said objective process for acase that said objective process has said pre-sequential order limitedprocess and set a starting date of estimated starting date of saidprocess as a reference for starting date of said objective process for acase that said objective process does not have said pre-sequential orderlimited process, to extract information of probability distributionmodel of a variance of starting date from said forecast modelinformation of said project, to compute a standard normalized randomnumber set by a simulation based on a variance of starting date, tocompute a reference for a variance by using said standard normalizedrandom number set, to judge whether said reference for a variance is ina range of a variance of starting date based on said forecast modelinformation of said project so that adding said reference for varianceas a variance of starting date to said reference for starting date for acase that said reference for a variance is in a range of a variance ofstarting date and said step to compute an estimate of starting date assaid at least one of parameters has further functions to compute anestimate of workdays by multiplying said estimate of elementary unitwith an estimated materials in said process planning and to add saidestimate of workdays to said estimate of starting date and estimate ofending date is obtained in said steps therein.
 17. A project assessmentmethod as defined in claim 15, wherein a step to compute an estimate ofstarting date as said at least one of parameters has functions to judgewhether a objective process has a pre-sequential order limited processby using information of said process planning and to resultantly set anending date of said pre-sequential order limited process as a referencefor starting date of said objective process for a case that saidobjective process has said pre-sequential order limited process and seta starting date of estimated starting date of said process as areference for starting date of said objective process for a case thatsaid objective process does not have said pre-sequential order limitedprocess, to extract information of probability distribution model of avariance of starting date from said forecast model information of saidproject, to compute a standard normalized random number set by asimulation based on a variance of starting date, to compute a referencefor a variance by using said standard normalized random number set, tojudge whether said reference for a variance is in a range of a varianceof starting date based on said forecast model information of saidproject so that adding said reference for variance as a variance ofstarting date to said reference for starting date for a case that saidreference for a variance is in a range of a variance of starting dateand said step to compute an estimate of starting date as said at leastone of parameters has further functions to compute an estimate ofworkdays by multiplying said estimate of elementary unit with anestimated materials in said process planning and to add said estimate ofworkdays to said estimate of starting date and an estimate of endingdate is obtained in said steps therein, and wherein said estimate ofstaring date and said estimate of ending date are judged whether saidtwo estimates satisfy critical term of said process planning so that aamendment is done for said estimates to satisfy said critical term for acase that said two estimates do not satisfy critical term of saidprocess planning.
 18. A project assessment method as defined in claim15, wherein a step to compute an estimate of starting date as said atleast one of parameters has functions to judge whether a objectiveprocess has a pre-sequential order limited process by using informationof said process planning and to resultantly set an ending date of saidpre-sequential order limited process as a reference for starting date ofsaid objective process for a case that said objective process has saidpre-sequential order limited process and set a starting date ofestimated starting date of said process as a reference for starting dateof said objective process for a case that said objective process doesnot have said pre-sequential order limited process, to extractinformation of probability distribution model of a variance of startingdate from said forecast model information of said project, to compute astandard normalized random number set by a simulation based on avariance of starting date, to compute a reference for a variance byusing said standard normalized random number set, to judge whether saidreference for a variance is in a range of a variance of starting datebased on said forecast model information of said project so that addingsaid reference for variance as a variance of starting date to saidreference for starting date for a case that said reference for avariance is in a range of a variance of starting date and said step tocompute an estimate of starting date as said at least one of parametershas functions to compute an estimate of workdays by multiplying saidestimate of elementary unit with an estimated materials in said processplanning and to add said estimate of workdays to said estimate ofstarting date and estimate of ending date is obtained in said stepstherein, and wherein said estimate of staring date and said estimate ofending date are judged whether said two estimates satisfy critical termof said process planning so that a amendment is done for said estimatesto satisfy said critical term for a case that said two estimates do notsatisfy critical term of said process planning and said step to computean estimate of man-days as said at least one of parameters has furtherfunctions to compute an estimate of man-days by multiplying saidestimate of elementary unit with an estimated materials and thendividing with said amended estimate of workdays obtained by saidestimate of workdays, and estimate of man-days is obtained in said stepstherein.